Skip to Content
SciPy Recipes
book

SciPy Recipes

by Luiz Felipe Martins, Ke Wu, Ruben Oliva Ramos, V Kishore Ayyadevara
December 2017
Intermediate to advanced
386 pages
10h 42m
English
Packt Publishing
Content preview from SciPy Recipes

Computing a function for all elements of an array

All scalar functions defined in NumPy follow the ufunc protocol, so that when applied to an array, they are applied to every array item. The following example shows you how to compute the sine function for all elements of a one-dimensional array:

x = np.pi * np.arange(0, 2, 0.25)y = np.sin(x)

In this code, we first create an array x with equally spaced values. Then, with the np.sin(x) expression, we compute an array y containing the value of the sine function evaluated at each item of the array x

It is important to notice that ufunc functions will operate on arrays with an arbitrary number of dimensions. For a unary ufunc, that is, a function that admits a single argument, the shape of the ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

Read now

Unlock full access

More than 5,000 organizations count on O’Reilly

AirBnbBlueOriginElectronic ArtsHomeDepotNasdaqRakutenTata Consultancy Services

QuotationMarkO’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.
Julian F.
Head of Cybersecurity
QuotationMarkI wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.
Addison B.
Field Engineer
QuotationMarkI’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.
Amir M.
Data Platform Tech Lead
QuotationMarkI'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Mark W.
Embedded Software Engineer

You might also like

Elegant SciPy

Elegant SciPy

Juan Nunez-Iglesias, Stéfan van der Walt, Harriet Dashnow
Matplotlib 3.0 Cookbook

Matplotlib 3.0 Cookbook

Srinivasa Rao Poladi, Nikhil Borkar
Mastering SciPy

Mastering SciPy

Francisco Javier Blanco-Silva, Francisco Javier B Silva

Publisher Resources

ISBN: 9781788291460